def deform_point_cloud(point_cloud,
strike,
dip,
d=0.01,
u_ss=1.0,
u_ds=1.0,
x0=None,
y0=None):
from utils import get_xyz_from_pdal, put_xyz_to_pdal
from pml import read_file
xyz = get_xyz_from_pdal(read_file(point_cloud)) if isinstance(point_cloud, str) else \
get_xyz_from_pdal(point_cloud[0]) if isinstance(point_cloud, list) else point_cloud if point_cloud.dtype.fields \
is None else get_xyz_from_pdal(point_cloud)
x = xyz[:, 0]
y = xyz[:, 1]
x0 = np.mean(x) if x0 is None else x0
y0 = np.mean(y) if y0 is None else y0
xt = x - x0
yt = y - y0
deltarad = np.deg2rad(dip)
thetarad = np.deg2rad(strike)
X1p = xt * np.cos(np.pi - thetarad) + yt * np.sin(np.pi - thetarad)
Zeta = (X1p / d) - (1 / np.tan(deltarad))
u1 = (u_ds / np.pi) * (np.cos(deltarad) * np.arctan(Zeta) +
(np.sin(deltarad) - Zeta * np.cos(deltarad)) /
(1 + np.power(Zeta, 2)))
u3 = (-u_ds / np.pi) * (np.sin(deltarad) * np.arctan(Zeta) +
(np.cos(deltarad) + Zeta * np.sin(deltarad)) /
(1 + np.power(Zeta, 2)))
u2 = (u_ss / np.pi) * (
np.arctan2(Zeta * np.power(np.sin(deltarad), 2),
(1 - Zeta * np.sin(deltarad) * np.cos(deltarad))) +
(deltarad - np.sign(deltarad) * np.pi / 2.0))
u1p = u1 * np.cos(thetarad - np.pi) + u2 * np.sin(thetarad - np.pi)
u2p = -u1 * np.sin(thetarad - np.pi) + u2 * np.cos(thetarad - np.pi)
deformed_points = xyz + np.vstack((u1p, u2p, u3)).T
return put_xyz_to_pdal(read_file(point_cloud), deformed_points) if isinstance(point_cloud, str) else \
list(put_xyz_to_pdal(point_cloud[0])) if isinstance(point_cloud, list) \
else put_xyz_to_pdal(point_cloud) if point_cloud.dtype.fields is not None else deformed_points
def test_dislocation(filename='hsl_101419_small.las',
strike=320,
dip=30,
ss=20.0,
ds=0.0,
d=0.01):
from dislocation import deform_point_cloud
from utils import get_xyz_from_pdal
import matplotlib.pylab as plt
pointcloud = get_xyz_from_pdal(pml.read_file(filename))
pointcloud = pointcloud[0::1000, :]
deformed_pointcloud = get_xyz_from_pdal(
deform_point_cloud(filename, strike, dip, u_ss=ss, u_ds=ds,
d=d))[0::1000, :]
plt.figure()
plt.plot(pointcloud[:, 0], pointcloud[:, 1], 'k.')
plt.figure()
plt.plot(deformed_pointcloud[:, 0], deformed_pointcloud[:, 1], 'k.')
plt.show()
def test_two_rotations(fixed, moving):
from pml import icp, read_file, transform_pdal_array
from utils import get_xyz_from_pdal
fixed_array = read_file(fixed)
moving_array = read_file(moving)
transformed_array, (transform_matrix, center,
residual) = icp(fixed_array, moving_array)
# perform second transformation:
center_2 = center - 50.0
transformed_array = transform_pdal_array(transformed_array,
transform_matrix,
center=center_2)
# manually rotate moving points back:
xyz_transformed = get_xyz_from_pdal(transformed_array)
xyz_moving = get_xyz_from_pdal(moving_array) - center
xyz_moving = np.concatenate((xyz_moving, np.ones(
(xyz_moving.shape[0], 1))),
axis=1)
xyz_manual_transform = np.matmul(xyz_moving,
transform_matrix.T)[:, 0:3] + center
xyz_manual_transform = np.concatenate(
(xyz_manual_transform - center_2,
np.ones((xyz_manual_transform.shape[0], 1))),
axis=1)
xyz_manual_transform = np.matmul(xyz_manual_transform,
transform_matrix.T)[:, 0:3] + center_2
return xyz_transformed, xyz_manual_transform
def test_one_rotation(fixed, moving):
from pml import icp, read_file
from utils import get_xyz_from_pdal
fixed_array = read_file(fixed)
moving_array = read_file(moving)
transformed_array, (transform_matrix, center,
residual) = icp(fixed_array, moving_array)
# manually rotate moving points back:
xyz_transformed = get_xyz_from_pdal(transformed_array)
xyz_moving = get_xyz_from_pdal(moving_array) - center
xyz_moving = np.concatenate((xyz_moving, np.ones(
(xyz_moving.shape[0], 1))),
axis=1)
xyz_manual_transform = np.matmul(xyz_moving,
transform_matrix.T)[:, 0:3] + center
return xyz_transformed, xyz_manual_transform
def create_test_dataset(in_pt_cloud_filename=None,
x_a=1E-3,
x_b=0.5E-3,
x_c=-1.2E-3,
x_d=-0.8E-1,
x_e=-1.0E-1,
x_f=1.0,
y_a=-1.5E-4,
y_b=-1.0E-4,
y_c=0.72E-3,
y_d=0.75E-1,
y_e=1.4E-1,
y_f=-1.0,
z_a=1E-4,
z_b=-4E-4,
z_c=-6E-4,
z_d=-1E-1,
z_e=1E-1,
z_f=1.0):
from utils import get_xyz_from_pdal, put_xyz_to_pdal
from pml import read_file
if in_pt_cloud_filename is None:
in_pt_cloud = read_file('clip_small.txt')
else:
in_pt_cloud = read_file(in_pt_cloud_filename)
xyz = get_xyz_from_pdal(in_pt_cloud)
xyzm = np.mean(xyz, axis=0)
xyz -= xyzm
x = xyz[:, 0]
y = xyz[:, 1]
z = xyz[:, 2]
dx = x_a * np.power(x, 2) + x_b * x * y + x_c * np.power(
y, 2) + x_d * x + x_e * y + x_f
dy = y_a * np.power(x, 2) + y_b * x * y + y_c * np.power(
y, 2) + y_d * x + y_e * y + y_f
dz = z_a * np.power(x, 2) + z_b * x * y + z_c * np.power(
y, 2) + z_d * x + z_e * y + z_f
xyz[:, 0] += dx
xyz[:, 1] += dy
xyz[:, 2] += dz
return put_xyz_to_pdal(in_pt_cloud, xyz + xyzm)
def create_test_grid(in_pt_cloud,
dx=10,
dy=10,
x_a=1E-3,
x_b=0.5E-3,
x_c=-1.2E-3,
x_d=-0.8E-1,
x_e=-1.0E-1,
x_f=1.0,
y_a=-1.5E-4,
y_b=-1.0E-4,
y_c=0.72E-3,
y_d=0.75E-1,
y_e=1.4E-1,
y_f=-1.0,
z_a=1E-4,
z_b=-4E-4,
z_c=-6E-4,
z_d=-1E-1,
z_e=1E-1,
z_f=1.0):
from pml import get_bounds
from utils import get_xyz_from_pdal
bounds = get_bounds(in_pt_cloud)
xyz = get_xyz_from_pdal(in_pt_cloud)
xyzm = np.mean(xyz, axis=0)
x = np.arange(bounds[0][0], bounds[0][1], dx) - xyzm[0]
y = np.arange(bounds[1][0], bounds[1][1], dy) - xyzm[1]
[x, y] = np.meshgrid(x, y)
ux = x_a * np.power(x, 2) + x_b * x * y + x_c * np.power(
y, 2) + x_d * x + x_e * y + x_f
uy = y_a * np.power(x, 2) + y_b * x * y + y_c * np.power(
y, 2) + y_d * x + y_e * y + y_f
uz = z_a * np.power(x, 2) + z_b * x * y + z_c * np.power(
y, 2) + z_d * x + z_e * y + z_f
return x, y, ux, uy, uz